Project: Data Migration of on-premise applications to AWSEntitlement: Data Engineer, Architecting Data Solution covering aspects of Analysis, Data management Solution Design, Data Consumption Layer Design (Reporting, Visualization), Data Governance, Metadata Management, Solution Implementation and Production DeploymentMy Responsibilities:• Data Solution Architectural Design and Orchestrationo Design, Propose and implement solutions to migrate on-premise applications to cloudo Analyze and define architecture changes to existing systems (EDW, CRM, and Integration batch) to incorporate new business requirements• Design & development of Enterprise ETL framework for Batch Integration & EDW Batch Solution• Design & Implement Data Lake & Data Warehousing architectures on the S3 data files in AWS creating parquet files in Redshift spectrum DB that flows through staging using AWS Lambda and AWS Glue services.Skills: AWS Glue, S3, Datalake, Lambda, Step Function, Python, ETL, Informatica Power Center

Designed and implemented data pipelines for seamless integration of healthcare data across multiple systems, enhancing interoperability and data accessibility. Developed ETL processes to aggregate and transform clinical and administrative data from diverse healthcare sources, ensuring data accuracy and consistency. Utilized HL7, FHIR, and other healthcare data standards to facilitate smooth data exchange between electronic health record (EHR) systems. Developed and maintained data warehouses and data lakes to support large-scale healthcare data storage and analysis. Employed AWS cloud and big data technologies to enhance scalability and performance of data processing tasks. Designed and implemented scalable data pipelines to support dynamic network configurations, enhancing flexibility and responsiveness in healthcare data management. Conducted performance tuning and optimization of SQL queries and database systems to improve data processing efficiency and network performance.